Update README.md

README.md

@@ -5,7 +5,6 @@ language:
 library_name: transformers
 tags:
 - linformer
-- legal
 - medical
 - RoBERTa
 - pytorch
@@ -29,7 +28,7 @@ Jargon is available in several versions with different context sizes and types o
 | jargon-general-legal                                                                |   jargon-general-base   |18GB Legal Corpus
 | [jargon-multidomain-base](https://huggingface.co/PantagrueLLM/jargon-multidomain-base) |   jargon-general-base   |Medical+Legal Corpora|
 | jargon-legal                                                                        |         scratch         |18GB Legal Corpus|
-| jargon-legal-4096                                                                   |         scratch         |18GB Legal Corpus|
+| [jargon-legal-4096](https://huggingface.co/PantagrueLLM/jargon-legal-4096)            |         scratch         |18GB Legal Corpus|
 | [jargon-biomed](https://huggingface.co/PantagrueLLM/jargon-biomed)                    |         scratch         |5.4GB Medical Corpus|
 | [jargon-biomed-4096](https://huggingface.co/PantagrueLLM/jargon-biomed-4096)          |         scratch         |5.4GB Medical Corpus|
 | [jargon-NACHOS](https://huggingface.co/PantagrueLLM/jargon-NACHOS)                    |         scratch         |[NACHOS](https://drbert.univ-avignon.fr/)|
@@ -45,7 +44,7 @@ For more info please check out the [paper](https://hal.science/hal-04535557/file
 
 ## Using Jargon models with HuggingFace transformers
 
-You can get started with `jargon-general-biomed` using the code snippet below:
+You can get started with this model using the code snippet below:
 
 ```python
 from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline